Strategies used by Patients with Type 1 Diabetes to Avoid Hypoglycemia in a 24×1-Hour Marathon: Comparison with the Amounts of Carbohydrates Estimated by a Customizable Algorithm

Effectiveness of a hybrid closed-loop system for children and adolescents with type 1 diabetes during physical exercise: A cross-sectional study in real life

OBJECTIVE

The aim of the study was to describe how physical exercise affects metabolic control, insulin requirements and carbohydrate intake in children who use hybrid closed-loop systems.

METHODS

Cross-sectional study design. The sample included 21 children and adolescents diagnosed with type 1 diabetes. During the study, participants were monitored for a period of 7 days to gather comprehensive data on these factors.

RESULTS

Nine participants (42.9%) had switched to exercise mode to raise the target glucose temporarily to 150 mg/dL. The HbA1c values ranged from 5.5% to 7.9% (median, 6.5%; IQR, 0.75). The percentage of time within the target range of 70-180 mg/dL was similar; however, there was an increased duration of hyperglycaemia and more autocorrections on exercise days. The time spent in severe hyperglycaemia (>250 mg/dL) increased by 2.7% in exercise compared to non-exercise days (P = .02). It is worth noting that hypoglycaemic episodes did not increase during the exercise days compared with non-exercise days.

CONCLUSION

The hybrid closed-loop system was effective and safe in children and adolescents with type 1 diabetes during the performance of competitive sports in real life.

Flash Glucose Monitoring in Croatia: The Optimal Number of Scans per Day to Achieve Good Glycemic Control in Type 1 Diabetes

Background and Objectives: The purpose of this study is to determine the optimal number of scans per day required for attaining good glycemic regulation. Materials and Methods: The association of scanning frequency and glucometrics was analyzed according to bins of scanning frequency and bins of time in range (TIR) in the Croatian population of type 1 diabetes (T1DM) patients. Results: Intermittently scanned continuous glucose monitoring (isCGM) Libre users in Croatia performed on average 13 ± 7.4 scans per day. According to bins of scanning frequency, bin 5 with 11.2 ± 02 daily scans was sufficient for achieving meaningful improvements in glycemic regulation, while decreasing severe hypoglycemia required an increasing number of scans up to bin 10 (31 ± 0.9), yet with no effect on TIR improvement. When data were analyzed according to bins of TIR, an average of 16.3 ± 10.5 scans daily was associated with a TIR of 94.09 ± 3.49% and a coefficient of variation (CV) of 22.97 ± 4.94%. Improvement was shown between each successive bin of TIR but, of notice, the number of scans performed per day was 16.3 ± 10.5 according to TIR-based analysis and 31.9 ± 13.5 in bin 10 according to scan frequency analysis. Conclusions: In conclusion, an optimal average number of scans per day is 16.3 in order to achieve glucose stability and to minimize the burden associated with over-scanning.

Post-Exercise Protein Intake May Reduce Time in Hypoglycemia Following Moderate-Intensity Continuous Exercise among Adults with Type 1 Diabetes

Little is known about the role of post-exercise protein intake on post-exercise glycemia. Secondary analyses were conducted to evaluate the role of post-exercise protein intake on post-exercise glycemia using data from an exercise pilot study. Adults with T1D (n = 11), with an average age of 33.0 ± 11.4 years and BMI of 25.1 ± 3.4, participated in isoenergetic sessions of high-intensity interval training (HIIT) or moderate-intensity continuous training (MICT). Participants completed food records on the days of exercise and provided continuous glucose monitoring data throughout the study, from which time in range (TIR, 70-180 mg/dL), time above range (TAR, >180 mg/dL), and time below range (TBR, <70 mg/dL) were calculated from exercise cessation until the following morning. Mixed effects regression models, adjusted for carbohydrate intake, diabetes duration, and lean mass, assessed the relationship between post-exercise protein intake on TIR, TAR, and TBR following exercise. No association was observed between protein intake and TIR, TAR, or TBR (p-values ≥ 0.07); however, a borderline significant reduction of -1.9% (95% CI: -3.9%, 0.0%; p = 0.05) TBR per 20 g protein was observed following MICT in analyses stratified by exercise mode. Increasing post-exercise protein intake may be a promising strategy to mitigate the risk of hypoglycemia following MICT.

Current Technologies for Managing Type 1 Diabetes Mellitus and Their Impact on Quality of Life-A Narrative Review

Type 1 diabetes mellitus is a chronic autoimmune disease that affects millions of people and generates high healthcare costs due to frequent complications when inappropriately managed. Our paper aimed to review the latest technologies used in T1DM management for better glycemic control and their impact on daily life for people with diabetes. Continuous glucose monitoring systems provide a better understanding of daily glycemic variations for children and adults and can be easily used. These systems diminish diabetes distress and improve diabetes control by decreasing hypoglycemia. Continuous subcutaneous insulin infusions have proven their benefits in selected patients. There is a tendency to use more complex systems, such as hybrid closed-loop systems that can modulate insulin infusion based on glycemic readings and artificial intelligence-based algorithms. It can help people manage the burdens associated with T1DM management, such as fear of hypoglycemia, exercising, and long-term complications. The future is promising and aims to develop more complex ways of automated control of glycemic levels to diminish the distress of individuals living with diabetes.

Insulin pumps in children - a systematic review

BACKGROUND

Insulin pump therapy is a real breakthrough in managing diabetes Mellitus, particularly in children. It can deliver a tiny amount of insulin and decreases the need for frequent needle injections. It also helps to maintain adequate and optimal glycemic control to reduce the risk of metabolic derangements in different tissues. Children are suitable candidates for pump therapy as they need a more freestyle and proper metabolic control to ensure adequate growth and development. Therefore, children and their caregivers should have proper education and training and understand the proper use of insulin pumps to achieve successful pump therapy. The pump therapy continuously improves to enhance its performance and increase its simulation of the human pancreas. Nonetheless, there is yet a long way to reach the desired goal.

AIM

To review discusses the history of pump development, its indications, types, proper use, special conditions that may enface the children and their families while using the pump, its general care, and its advantages and disadvantages.

METHODS

We conducted comprehensive literature searches of electronic databases until June 30, 2022, related to pump therapy in children and published in the English language.

RESULTS

We included 118 articles concerned with insulin pumps, 61 were reviews, systemic reviews, and meta-analyses, 47 were primary research studies with strong design, and ten were guidelines.

CONCLUSION

The insulin pump provides fewer needles and can provide very tiny insulin doses, a convenient and more flexible way to modify the needed insulin physiologically, like the human pancreas, and can offer adequate and optimal glycemic control to reduce the risk of metabolic derangements in different tissues.

Personalized Approach for the Management of Exercise-Related Glycemic Imbalances in Type 1 Diabetes: Comparison with Reference Method

BACKGROUND

One of the most frequently adopted strategies to counterbalance the risk of exercise-induced hypoglycemia in patients with type 1 diabetes is carbohydrates supplement. Nevertheless, the estimation of its amount is still challenging. We investigated the efficacy of the personalized Exercise Carbohydrate Requirement Estimation System (ECRES) method compared to a tabular approach to estimate the glucose supplement needed for the prevention of exercise-related glycemic imbalances.

METHOD

Twenty-six patients performed two one-hour constant intensity exercises one week apart; the amount of extra carbohydrates was estimated, in random order, by the personalized ECRES method or through the tabular approach; glycemia was determined every 30 minutes. Continuous glucose monitoring (CGM) metrics were calculated over the 48 hours preceding, and the afternoon and night following the trials.

RESULTS

Applying the personalized ECRES method, a significantly lower amount of carbohydrates was administered to the active patients compared to the tabular approach, median (interquartile range): 9.0 (0.5-21.0) g vs 23.0 (21.0-25.0) g; P < .01; the two methods were similar for the sedentary patients, 18 (13.5-36.0) g vs 23.0 (21.0-27.0) g; P = NS. After overlapping CGM metrics before the exercises, both methods avoided hypoglycemia and resulted in similar glucose levels throughout them. The ECRES method led to CGM metrics within the guidelines for either the afternoon and the night just following the trials, whereas the tabular approach resulted in a significantly greater time below range in the afternoon (11.8% ± 18.2%; P < .05) and time above range during the night (39.3% ± 29.8%; P < .05).

CONCLUSIONS

The results support the validity of the personalized ECRES method: although the estimated amounts of carbohydrates were lower, patients' glycemia was maintained within safe clinical limits.

Comparison of two carbohydrate intake strategies to improve glucose control during exercise in adolescents and adults with type 1 diabetes

BACKGROUND AND AIMS

During aerobic physical activity (PA), hypoglycemia is common in people with type 1 diabetes (T1D). Few studies have compared the effectiveness of different carbohydrate (CHO) intake strategies to prevent PA-induced hypoglycemia. Our objective was to compare the efficacy of two CHO intake strategies, same total amount but different CHO intake timing, to maintain glucose levels in the target range (4.0-10.0 mmol/L) during PA in people with T1D.

METHODS AND RESULTS

An open-label, randomized, crossover study in 33 participants (21 adults; 12 adolescents). Participants practiced 60 min PA sessions (ergocyle) at 60% VO_2peak 3.5 h after lunch comparing an intake of 0.5 g of CHO per kg of body weight applied in a pre-PA single CHO intake (SCI) or in a distributed CHO intake (DCI) before and during PA. The percentage of time spent in glucose level target range during PA was not different between the two strategies (SCI: 75 ± 35%; DCI: 87 ± 26%; P = 0.12). Hypoglycemia (<4.0 mmol/L) occurred in 4 participants (12%) with SCI compared to 6 participants (18%) with DCI (P = 0.42). The SCI strategy led to a higher increase (P = 0.01) and variability of glucose levels (P = 0.04) compared with DCI.

CONCLUSIONS

In people living with T1D, for a 60 min moderate aerobic PA in the post-absorptive condition, a 0.5 g/kg CHO intake helped most participants maintain acceptable glycemic control with both strategies. No clinically significant difference was observed between the SCI and DCI strategies. ClinicalTrials.gov Identifier: NCT03214107 (July 11, 2017).

Carbohydrate Requirement for Exercise in Type 1 Diabetes: Effects of Insulin Concentration

Physical activity is a keystone of a healthy lifestyle as well as of management of patients with type 1 diabetes. The risk of exercise-induced hypoglycemia, however, is a great challenge for these patients. The glycemic response to exercise depends upon several factors concerning the patient him/herself (eg, therapy, glycemic control, training level) and the characteristics of the exercise performed. Only in-depth knowledge of these factors will allow to develop individualized strategies minimizing the risk of hypoglycemia. The main factors affecting the exercise-induced hypoglycemia in patients with T1D have been analyzed, including the effects of insulin concentration. A model is discussed, which has the potential to become the basis for providing patients with individualized suggestions to keep constant glucose levels on each exercise occasion.

Factors associated with fear of hypoglycaemia among the T1D Exchange Glu population in a cross-sectional online survey

OBJECTIVES

Fear of hypoglycaemia (FoH) has been associated with suboptimal diabetes management and health outcomes. This study investigated factors associated with behavioural and emotional aspects of FoH among adults living with type 1 diabetes (T1D) mellitus.

DESIGN

Cross-sectional study.

SETTING

Online survey hosted on T1D Exchange Glu, an online community for patients living with T1D mellitus.

MEASURES

The Hypoglycaemia Fear Survey II-short form and the Hypoglycaemic Attitudes and Behaviour Scale were used to assess FoH. Multivariable regressions were performed on assessment scores.

RESULTS

The study included 494 participants (mean±SD age 43.9±12.2 years, duration of T1D mellitus 16.6±16.8 years, self-reported glycosylated hemoglobin (HbA1c) 6.9%±0.8% (52±9 mmol/mol)), 63% men, 89% on insulin pump, 25% experienced a severe hypoglycaemic event in the last 6 months. Multivariable regression analyses showed higher anxiety, depression severity and diabetes distress were independently associated with FoH (all p<0.01). Longer diabetes duration was associated with lower FoH (p<0.01). Past experience with severe hypoglycaemia was associated with higher worry of hypoglycaemia (p<0.01) but not avoidance behaviour (ns).

CONCLUSIONS

These results highlighted the multifaceted nature of FoH, which warrants further discussion between providers and patients to uncover drivers of and actions required to reduce FoH and improve patient care and outcomes.

Diabetes Technology and Exercise

Advances in technologies such as glucose monitors, exercise wearables, closed-loop systems, and various smartphone applications are helping many people with diabetes to be more physically active. These technologies are designed to overcome the challenges associated with exercise duration, mode, relative intensity, and absolute intensity, all of which affect glucose homeostasis in people living with diabetes. At present, optimal use of these technologies depends largely on motivation, competence, and adherence to daily diabetes care requirements. This article discusses recent technologies designed to help patients with diabetes to be more physically active, while also trying to improve glucose control around exercise.

Carbohydrate Intake in the Context of Exercise in People with Type 1 Diabetes

Although the benefits of regular exercise on cardiovascular risk factors are well established for people with type 1 diabetes (T1D), glycemic control remains a challenge during exercise. Carbohydrate consumption to fuel the exercise bout and/or for hypoglycemia prevention is an important cornerstone to maintain performance and avoid hypoglycemia. The main strategies pertinent to carbohydrate supplementation in the context of exercise cover three aspects: the amount of carbohydrates ingested (i.e., quantity in relation to demands to fuel exercise and avoid hypoglycemia), the timing of the intake (before, during and after the exercise, as well as circadian factors), and the quality of the carbohydrates (encompassing differing carbohydrate types, as well as the context within a meal and the associated macronutrients). The aim of this review is to comprehensively summarize the literature on carbohydrate intake in the context of exercise in people with T1D.

Glycaemic stability of a cyclist with Type 1 diabetes: 4011 km in 20 days on a ketogenic diet

BACKGROUND

Maintaining glycaemic control during exercise presents a significant challenge for people living with Type 1 diabetes. Significant glycaemic variability has been observed in athletes with Type 1 diabetes in competitive contexts. While very-low-carbohydrate ketogenic diets have been shown to minimize glycaemic excursions, no published data have examined if this translates to exercise.

CASE REPORT

We report the case of a 37-year-old man with Type 1 diabetes who successfully undertook a 4011 km cycle across Australia over 20 consecutive days whilst consuming a very-low-carbohydrate ketogenic diet. Continuous glucose monitoring data capture was 98.4% for the ride duration and showed remarkable glycaemic stability, with a standard deviation of 2.1 mmol/l (average interstitial glucose 6.1 mmol/l) and 80.4% of time spent within a range of 3.9-10 mmol/l. Interstitial glucose was <3 mmol/l for 2.1% of this time, with only a single episode of symptomatic hypoglycaemia prompting brief interruption of exercise for carbohydrate administration.

CONCLUSION

This case demonstrates the viability of a very-low-carbohydrate ketogenic diet in an individual with Type 1 diabetes undertaking exercise. While the effect of a very-low-carbohydrate ketogenic diet is yet to be examined more broadly in athletes with Type 1 diabetes, the glycaemic stability observed suggests that fat adaptation may attenuate glycaemic swings and reduce reliance on carbohydrate consumption during exercise for maintaining euglycaemia.

Fluid Intake Habits in Type 1 Diabetes Individuals during Typical Training Bouts

BACKGROUND/AIMS

Hyperglycemia may influence the hydration status in diabetic individuals. During exercise, type 1 diabetes mellitus (T1DM) individuals may be challenged by a higher risk of dehydration due to a combination of fluid losses from sweat and increased urine output via glycosuria. So far, no study has characterised spontaneous fluid intake in T1DM individuals during active trainings.

METHODS

A validated questionnaire was used to assess T1DM participants' diabetes therapy, sports characteristics and fluid intake during training; results were then compared to an age- and sport-matched sample of non-diabetic individuals.

RESULTS

Ninety individuals completed the survey (n = 45 T1DM individuals, n = 45 matched controls). A proportion of T1DM -individuals reported blood glucose levels greater than 10.0 mmol at both the start (28.9%) and end (24.4%) of the exercise. The mean self-reported fluid intake was greater in T1DM (0.60 ± 0.47 L·h-1) compared to that of the control (0.37 ± 0.28 L·h-1, p < 0.05). In spite of drinking fluid volumes in line with international guidelines, 84.4% of those with T1DM reported that they were still feeling thirsty at the end of their training session.

CONCLUSIONS

T1DM individuals self-report spontaneously consuming fluid adequate volumes suggested by sport nutrition guidelines for non-diabetic athletes. Discrepancies in the T1DM subjectively reported feelings of thirst suggest that more education on hydration during exercise is needed for this population to adequately compensate for elevated blood glucose levels. It remains to be established whether fluid volumes suggested for healthy athletes are adequate for maintaining euhydration in T1DM patients due to their altered diuresis.

Assessment of Mitigation Methods to Reduce the Risk of Hypoglycemia for Announced Exercise in a Uni-hormonal Artificial Pancreas

BACKGROUND

Moderate physical activity improves overall health conditions in subjects with type 1 diabetes. However, insulin management during and after exercise is challenging due to the effects of exercise on glycemic control. Artificial pancreas (AP) systems aim to automatically control blood glucose levels, but exercise-induced hypoglycemia is a major challenge for these systems, especially in uni-hormonal configurations. The aim of this work was to evaluate the ability of several feed-forward (FF) actions to prevent exercise-induced hypoglycemia in a closed-loop setting.

METHODS

A closed-loop control algorithm combined with FF actions aimed at eliminating exercise-induced hypoglycemia was evaluated in silico using the UVa/Padova type 1 diabetes simulator. The simulator was modified with an exercise model fitted to clinical data. The FF actions were evaluated in two scenarios: (1) exercise sessions during postprandial period and (2) exercise sessions during fasting period.

RESULTS

The mitigation methods proposed in this work were able to minimize the occurrence of hypoglycemic events related with exercise in both scenarios. The time spent in hypoglycemic range in the 2-h period after exercise decreased from 33.3% to 0.0% (P < 0.01) and from 41.3% to 0.0% (P < 0.01) in both scenarios tested. Besides that, the occurrence of hypoglycemic events after exercise sessions was also reduced.

CONCLUSIONS

The combination of the FF actions presented in this article within an AP system showed to be an effective strategy to mitigate the risk of hypoglycemia in front of aerobic exercise.